Methylation detection with nanopore sequencing: an introduction to Remora

Methylation plays a key role in gene expression, with abnormal methylation patterns strongly associated with many diseases, including cancer. Remora broadens access to direct, PCR-free nanopore sequencing that captures methylation across the whole genome.

This Knowledge Exchanged started off with an introduction to nanopore sequencing, including how the technology works and the benefits of direct, PCR-free methylation detection.

Then, Dr. Marcus Stoiber presented recent updates on methylation and modified base detection from nanopore data, including the latest Remora algorithms. These results show that nanopore sequencing is the new gold standard for methylation detection. New advancements will be presented on more recent developments in all-contexts modified base detection, including efforts towards 6mA detection and more. Best practices and updates on simplifying the modified base calling procedures will also be discussed.

Finally, Rocio Esteban shared examples of the applications of Remora for methylation analysis from the Oxford Nanopore Applications team.

To access the second part of the methylation Knowledge Exchange series covering RRMS, please click here.

Meet the speakers

Rocio Esteban is an Applications Support Bioinformatician at Oxford Nanopore. She completed a biotechnology degree in the University of Lleida and a Master’s degree in computational sciences in the University of Vigo. Prior to joining Oxford Nanopore, she worked as a Bioinformatics Specialist for a genomics company, helping to develop various bioinformatics pipelines including genotyping projects for population genomics studies, and genome assembly and annotation. She joined Oxford Nanopore 2.5 years ago, starting in the benchmarking team, where her work focused on methylation calling and germ-line and somatic SV calling general benchmarking, and also on adaptive sampling, helping to develop the Reduced-Representation Methylation Sequencing (RRMS) method. Recently, she started a new role, providing support in customer-facing projects.

Dr. Marcus Stoiber is a Principal Algorithms Researcher in the Machine Learning Research group developing algorithms and software for the accurate detection of methylation and modified bases from Oxford Nanopore data. He is the lead developer on the most recent Remora modified base detection algorithms. He completed his Master’s degree at Johns Hopkins University in bioinformatics, followed by a PhD at UC Berkely in biostatistcs completing his thesis on the analysis of multi-omics datasets. Dr. Stoiber then completed a post-doc at LBNL working in part on nanopore algorithms. He joined Oxford Nanopore in 2017 and has led the modified base detection development over the past 5 years.